Evidence map›Paper›PMID 40263320›Full record

ArticleScientific reports2025

Chemical applicability and predictive potential of certain graphical indices for determining structure-property relationships in polycrystalline acid magenta (C

Jiang-Hua Tang, Anila Hamraz, Asad Ullah, Y S Hamed, Shahid Zaman, Melaku Berhe Belay

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jiang-Hua TangDepartment of General Education, Anhui Xinhua University, Hefei, 230088, China.
Anila HamrazDepartment of Mathematical Sciences, Karakoram International University Gilgit-Baltistan, Gilgit, 15100, Pakistan.
Asad UllahDepartment of Mathematical Sciences, Karakoram International University Gilgit-Baltistan, Gilgit, 15100, Pakistan. dr.asadullah@kiu.edu.pk.
Y S HamedDepartment of Mathematics and Statistics, Collage of Science, Taif University, P.O. Box 11099, 21944, Taif, Saudi Arabia.
Shahid ZamanDepartment of Mathematical and Physical Sciences, College of Arts and Sciences, University of Nizwa, 616, Nizwa, Sultanate of Oman.
Melaku Berhe BelayNanotechnology Center of Excellence, Addis Ababa Science and Technology University, P.O.Box 16417, Addis Ababa, Ethiopia. melaku.berhe@aastu.edu.et.

Funding

Natural Science Foundation of Colleges and Universities in Anhui Province 2024AH050616Taif University, Saudi Arabia TU-DSPP-2024-47
6 · The paper itself

Abstract

Acid Magenta, also known as Fuchsine acid, is a polycrystalline material with an anorthic structure that stands out for its eco-friendliness, cost-effectiveness, and versatility. Widely used in histology for cellular differentiation and across various industrial applications, Acid Magenta's detailed molecular understanding and prediction of physicochemical properties hold significant value. Despite its relevance, research focused on the molecular topological modeling of Acid Magenta remains limited. This gap presents a unique opportunity to develop accurate and reliable topological descriptions of this molecular structure, which could significantly benefit industrial applications. This study aims to bridge the existing gap in topological modeling of Acid Magenta through a Quantitative Structure-Property Relationship (QSPR) and Quantitative Structure-Activity Relationship (QSAR) analysis, potentially enhancing its industrial utility. Utilizing efficient vertex partitioning techniques from chemical graph theory, we developed closed-form expressions for crucial topological descriptors, including the 1st multiplicative Zagreb index, 1st exponential Zagreb index, forgotten topological index, inverse degree index, 1st Zagreb index, multiplicative exponential Zagreb index and modified 1st Zagreb index. These derived indices were systematically evaluated to assess their impact on the structural properties of Acid Magenta. To further test predictive potential, the model applied linear fitting to key physicochemical properties of 18 octane isomers. Findings reveal that the indices 1st Zagreb index, Forgotten index, and Inverse degree index exhibit strong predictive correlations with these properties, particularly for entropy, the acentric factor, and enthalpy of vaporization (HVAP). The robust predictive performance of these indices underscores their potential as efficient alternatives to experimental testing for future QSAR/QSPR analysis, paving the way for new applications in environmental and industrial settings.

Indexed as

Computational analysisMolecular structureQSPRTopological modeling

Identifiers

PMID40263320
PMCPMC12015308

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